Elastic Search training courses
London UK & Live Online

JBI Training offers two courses in this group. Elasticsearch Engineer is a four-day comprehensive programme covering the full Elasticsearch stack for engineers who need to deploy, manage, and query Elasticsearch in production. Data Analysis with Kibana is a two-day course focused on using Kibana — Elasticsearch's visualisation and analytics layer — for data exploration, dashboard creation, and operational monitoring. Both courses are available as scheduled classroom sessions in London, as live online instructor-led training, or as customised onsite programmes for engineering and data teams.

Elasticsearch is an open-source, distributed search and analytics engine built on Apache Lucene and developed by Elastic. It is designed to store, search, and analyse large volumes of data in near real-time. It is widely used for full-text search across applications and websites, log and event data analysis, security information and event management (SIEM), application performance monitoring, e-commerce product search, and operational intelligence dashboards. Elasticsearch is the core component of the Elastic Stack (also known as the ELK Stack), which combines Elasticsearch with Logstash (data ingestion), Kibana (visualisation), and Beats (lightweight data shippers).

The four-day Elasticsearch Engineer course provides comprehensive coverage of Elasticsearch for engineers responsible for deploying, administering, and querying Elasticsearch in real environments. Topics include the Elasticsearch architecture and cluster model, indexing and mapping data, the Elasticsearch Query DSL for search and aggregation, data ingestion using Logstash and Beats, cluster management and administration, performance tuning and optimisation, security configuration, snapshot and restore for backup, and scaling Elasticsearch for production workloads. The course includes hands-on labs throughout and is suited to DevOps engineers, backend developers, data engineers, and infrastructure professionals who work with or are adopting Elasticsearch.

The two-day Data Analysis with Kibana course focuses on using Kibana — the visualisation and analytics front-end for the Elastic Stack — to explore, analyse, and present data stored in Elasticsearch. Topics covered include the Kibana interface and Discover tool for data exploration, creating visualisations including bar charts, line charts, maps, and metric panels, building and sharing interactive dashboards, using Kibana Lens for intuitive drag-and-drop analytics, working with time-series data, Canvas for pixel-perfect visual reporting, and an introduction to Kibana's machine learning and alerting features. It is suited to data analysts, operations teams, and DevOps professionals who need to derive insights and build monitoring dashboards from Elasticsearch data.

Traditional relational databases such as MySQL, PostgreSQL, and SQL Server store structured data in tables with defined schemas and are optimised for transactional workloads — inserting, updating, and retrieving records with precise queries. Elasticsearch is a document store optimised for full-text search, unstructured or semi-structured data, and analytical queries across very large datasets in near real-time. It excels at searching across free-text fields, handling variable data structures, and aggregating across millions of documents quickly. Many organisations use both — a relational database for transactional data and Elasticsearch as a search and analytics layer on top of that data, often populated via a data pipeline using Logstash or Beats.

Yes. Both courses can be delivered as customised onsite or online programmes for corporate engineering and data teams. Content and lab exercises can be tailored to the team's existing Elastic Stack version, deployment environment — whether on-premises, on Elastic Cloud, or hosted on AWS, Azure, or Google Cloud — and specific use cases such as log analytics, security monitoring, application search, or operational dashboards. JBI has delivered Elasticsearch and DevOps-related training for engineering teams at organisations including the BBC, NHS, RBS, Sky, EDF, and Cisco.

Yes. The Elastic Stack is updated regularly with new features across Elasticsearch, Kibana, Logstash, and Beats, and JBI's training content is continuously reviewed to reflect the latest stable release. This includes updates to Kibana Lens and the Kibana interface, new Elasticsearch query and aggregation capabilities, developments in Elastic's AI and machine learning features — including semantic search and vector search capabilities that are increasingly central to modern Elasticsearch deployments — and changes to Elastic's cloud and licensing model. Delegates learn skills that are current and applicable to the version of the Elastic Stack in use in their organisation today.